Global summary

Identifying changes in the reproduction number, rate of spread, and doubling time during the course of the COVID-19 outbreak whilst accounting for potential biases due to delays in case reporting both nationally and subnationally. These results are impacted by changes in testing effort, increases and decreases in testing effort will increase and decrease reproduction number estimates respectively (see Methods for further explanation).

Using data available up to the: 2020-04-12

Note that it takes time for infection to cause symptoms, to get tested for SARS-CoV-2 infection, for a positive test to return and ultimately to enter the case data presented here. In other words, today’s case data are only informative of new infections about two weeks ago. This is reflected in the plots below, which are by date of infection.

Expected daily confirmed cases by country


Figure 1: The results of the latest reproduction number estimates (based on estimated confirmed cases with a date of infection on the 2020-04-02) can be summarised by whether confirmed cases are likely increasing or decreasing. This represents the strength of the evidence that the reproduction number in each region is greater than or less than 1, respectively (see the methods for details). Countries with fewer than 100 confirmed cases reported on a single day are not included in the analysis (light grey) as there is not enough data to reliably estimate the reproduction number.

Summary of latest reproduction number and confirmed case count estimates by date of infection


Figure 1: Confirmed cases with date of infection on the 2020-04-02 and the time-varying estimate of the effective reproduction number (light bar = 90% credible interval; dark bar = the 50% credible interval.). Regions are ordered by the number of expected daily confirmed cases and shaded based on the expected change in daily confirmed cases. The dotted line indicates the target value of 1 for the effective reproduction no. required for control and a single case required for elimination.

Reproduction numbers over time in the six regions expected to have the most new confirmed cases


Figure 2: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of new confirmed cases. Estimates are shown up to the 2020-04-02. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The dotted line indicates the target value of 1 for the effective reproduction no. required for control.

Reported confirmed cases and their estimated date of infection in the six regions expected to have the most new confirmed cases


Figure 3: Confirmed cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of new confirmed cases. Estimates are shown up to the 2020-04-02. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence.

Reproduction numbers over time in all regions


Figure 4: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates are shown up to the 2020-04-02. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The dotted line indicates the target value of 1 for the effective reproduction no. required for control.

Reported confirmed cases and their estimated date of infection in all regions

Figure 5: Confirmed cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates are shown up to the 2020-04-02. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence.

Latest estimates (as of the 2020-04-02)

Table 1: Latest estimates (as of the 2020-04-02) of the number of confirmed cases by date of infection, the effective reproduction number, and the doubling time in each region. The mean and 90% credible interval is shown.
Country/Region New confirmed cases by infection date Expected change in daily cases Effective reproduction no. Doubling time (days)
Algeria 100 (53 – 137) Unsure 0.9 (0.7 – 1.1) -18 (24 – Inf)
Argentina 100 (52 – 148) Unsure 1 (0.7 – 1.3) -69 (11 – Inf)
Australia 110 (62 – 161) Decreasing 0.7 (0.5 – 0.8) -9.1 (Inf – Inf)
Austria 312 (249 – 383) Likely decreasing 0.9 (0.7 – 1) -38 (37 – Inf)
Azerbaijan 101 (52 – 147) Likely increasing 1.3 (1 – 1.7) 12 (5.1 – Inf)
Bahrain 71 (37 – 106) Increasing 1.4 (1 – 1.9) 9.3 (4.2 – Inf)
Bangladesh 88 (47 – 131) Increasing 2 (1.3 – 2.7) 4.4 (2.8 – 10)
Belarus 339 (268 – 408) Increasing 1.7 (1.4 – 2) 6 (4.5 – 9.1)
Belgium 1475 (1325 – 1622) Increasing 1.1 (1 – 1.1) 72 (26 – Inf)
Brazil 1864 (1708 – 2033) Increasing 1.3 (1.2 – 1.4) 13 (10 – 19)
Cameroon 44 (15 – 70) Likely decreasing 0.8 (0.4 – 1.1) -7.5 (56 – Inf)
Canada 1380 (1249 – 1542) Likely increasing 1.1 (1 – 1.1) 390 (37 – Inf)
Chile 437 (350 – 507) Increasing 1.1 (1 – 1.3) 30 (13 – Inf)
China 82 (39 – 122) Unsure 1.1 (0.8 – 1.4) 39 (6.9 – Inf)
Colombia 222 (160 – 273) Increasing 1.3 (1.1 – 1.6) 11 (6.4 – 42)
Czech Republic 308 (156 – 456) Unsure 1.1 (0.8 – 1.5) 27 (7.1 – Inf)
Czechia 238 (164 – 300) Unsure 1 (0.8 – 1.1) -60 (21 – Inf)
Denmark 277 (199 – 335) Unsure 1 (0.8 – 1.1) -53 (27 – Inf)
Dominican Republic 206 (155 – 262) Increasing 1.3 (1.1 – 1.6) 13 (6.9 – 320)
Ecuador 929 (813 – 1050) Increasing 1.8 (1.5 – 2.1) 5.6 (4.5 – 7.4)
Egypt 176 (112 – 241) Increasing 1.4 (1.1 – 1.7) 9.9 (5.4 – 62)
Estonia 47 (16 – 79) Unsure 0.9 (0.5 – 1.3) -15 (10 – Inf)
Finland 162 (106 – 214) Likely increasing 1.2 (1 – 1.4) 29 (8.8 – Inf)
France 4110 (3879 – 4355) Unsure 1 (1 – 1) 200 (42 – Inf)
Germany 4623 (4345 – 4854) Decreasing 0.9 (0.9 – 1) -39 (Inf – Inf)
Greece 75 (33 – 113) Unsure 1 (0.7 – 1.3) -44 (9.7 – Inf)
Hungary 136 (78 – 184) Increasing 1.5 (1.2 – 1.9) 7.2 (4.2 – 23)
India 752 (656 – 860) Increasing 1.3 (1.2 – 1.4) 16 (10 – 38)
Indonesia 262 (191 – 318) Increasing 1.3 (1.1 – 1.5) 14 (7.5 – 94)
Iran 1924 (1754 – 2085) Decreasing 0.9 (0.8 – 0.9) -19 (Inf – Inf)
Iraq 81 (38 – 129) Likely increasing 1.2 (0.8 – 1.5) 22 (5.8 – Inf)
Ireland 706 (604 – 803) Increasing 1.4 (1.2 – 1.5) 11 (7.7 – 18)
Israel 397 (318 – 467) Decreasing 0.8 (0.7 – 0.9) -11 (Inf – Inf)
Italy 3842 (3624 – 4097) Decreasing 0.9 (0.9 – 0.9) -43 (Inf – Inf)
Japan 415 (330 – 490) Increasing 1.2 (1.1 – 1.4) 19 (9.8 – 250)
Kazakhstan 64 (23 – 103) Unsure 1.2 (0.7 – 1.6) 26 (5.5 – Inf)
Kuwait 94 (49 – 136) Likely increasing 1.3 (0.9 – 1.6) 16 (5.7 – Inf)
Lithuania 51 (13 – 81) Unsure 1 (0.6 – 1.5) -45 (7.3 – Inf)
Luxembourg 101 (54 – 143) Unsure 0.9 (0.7 – 1.2) -28 (14 – Inf)
Malaysia 144 (85 – 193) Likely decreasing 0.9 (0.8 – 1.1) -24 (23 – Inf)
Mexico 352 (277 – 417) Increasing 1.3 (1.1 – 1.5) 13 (7.6 – 37)
Moldova 130 (78 – 173) Likely increasing 1.2 (0.9 – 1.5) 28 (8 – Inf)
Morocco 97 (50 – 141) Unsure 1.1 (0.8 – 1.4) 54 (7.9 – Inf)
Netherlands 1111 (980 – 1225) Likely increasing 1 (1 – 1.1) 67 (23 – Inf)
Norway 136 (81 – 195) Decreasing 0.8 (0.6 – 0.9) -11 (Inf – Inf)
Pakistan 259 (188 – 328) Unsure 1 (0.8 – 1.2) -860 (14 – Inf)
Panama 224 (156 – 283) Increasing 1.2 (1 – 1.4) 18 (8.4 – Inf)
Peru 834 (732 – 938) Increasing 1.6 (1.4 – 1.8) 6.7 (5.4 – 8.7)
Philippines 192 (136 – 253) Decreasing 0.9 (0.8 – 1) -20 (53 – Inf)
Poland 379 (304 – 447) Likely increasing 1.1 (0.9 – 1.2) 81 (17 – Inf)
Portugal 955 (838 – 1062) Increasing 1.1 (1 – 1.2) 26 (14 – 200)
Qatar 178 (116 – 236) Unsure 1 (0.8 – 1.2) 160 (12 – Inf)
Romania 348 (272 – 412) Likely increasing 1.1 (0.9 – 1.2) 100 (17 – Inf)
Russia 1416 (1278 – 1558) Increasing 1.4 (1.3 – 1.6) 9.5 (7.7 – 13)
Saudi Arabia 287 (221 – 349) Increasing 1.3 (1.1 – 1.5) 12 (7.2 – 42)
Serbia 233 (176 – 292) Likely increasing 1.1 (0.9 – 1.3) 58 (13 – Inf)
Singapore 166 (113 – 212) Increasing 1.4 (1.2 – 1.7) 8.3 (5 – 24)
Slovakia 73 (20 – 117) Likely increasing 1.5 (0.9 – 2.2) 8.1 (3.4 – Inf)
South Africa 91 (41 – 132) Likely increasing 1.2 (0.8 – 1.6) 16 (5.6 – Inf)
South Korea 60 (17 – 98) Likely decreasing 0.8 (0.5 – 1.1) -10 (18 – Inf)
Spain 5396 (5119 – 5687) Decreasing 0.9 (0.9 – 0.9) -23 (Inf – Inf)
Sweden 620 (523 – 715) Increasing 1.2 (1 – 1.3) 25 (13 – 7000)
Switzerland 675 (576 – 772) Decreasing 0.9 (0.8 – 0.9) -20 (Inf – Inf)
Thailand 74 (32 – 112) Likely decreasing 0.8 (0.6 – 1.1) -14 (19 – Inf)
Turkey 4195 (3924 – 4422) Increasing 1.2 (1.2 – 1.3) 17 (14 – 23)
Ukraine 229 (168 – 284) Increasing 1.3 (1.1 – 1.6) 12 (6.6 – 52)
United Arab Emirates 329 (260 – 396) Increasing 1.2 (1 – 1.4) 20 (9.7 – Inf)
United Kingdom 4723 (4486 – 4984) Increasing 1.1 (1.1 – 1.2) 68 (36 – 710)
United States of America 33561 (32887 – 34205) Increasing 1.1 (1.1 – 1.2) 55 (42 – 78)
Uzbekistan 65 (24 – 99) Likely increasing 1.3 (0.8 – 1.8) 15 (4.9 – Inf)

Corrections

If you see mistakes or want to suggest changes, please create an issue on the source repository.

Reuse

Text and figures are licensed under Creative Commons Attribution CC BY 4.0. Source code is available at https://github.com/epiforecasts/covid, unless otherwise noted. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".

© Copyright 2020 EpiForecasts and the CMMID Covid working group

Software licensed under the MIT License.